A System Dynamics Model to Analyze Development of Innovation Districts

This paper presents a System Dynamics (SD) model to analyze the development of innovation districts (ID), which have emerged as key drivers of knowledge-based urban economies. The model's construction draws on a comprehensive literature review, highlighting the significance of proximity dimensions in fostering knowledge creation and diffusion among district actors. By using causal loop diagrams (CLDs), the model captures the complex relationships and feedback loops across economic, social, governance, and urban dimensions. Validation against real ID cases demonstrates its accuracy and reliability as a decision-making tool. Simulation results reveal the impact of policies by Triple Helix actors (Government, Industry, and Academia) on the district's performance. The study emphasizes the Government's role in shaping infrastructure, Academia's role in talent supply, and Industry's influence on innovation. The research offers valuable insights for policymakers seeking to create thriving knowledge-based urban economies and drive sustainable economic growth within innovation districts. However, limitations in data quality and model complexity call for continuous updating and participatory modeling processes in future research.